DATA OPS
Snowflake column-drift sentinel to Slack
Snapshots the columns of your watched Snowflake tables on a schedule, compares against the last known shape, and posts a Slack alert when columns are added, dropped, or change…
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionRead column metadata from Snowflake INFORMATION_SCHEMASnowflake
- ActionLoad previous column snapshot from PostgresPostgres
- LogicDiff snapshots; branch only if columns changed
- OutputPost drift summary to Slack channelSlack
- ActionPersist new snapshot to PostgresPostgres
What it does
Keeps a fingerprint of every column in a list of critical Snowflake tables and tells you the moment that fingerprint changes — a renamed column, a dropped field, a `NUMBER` that became a `VARCHAR`. Catches the upstream change before your dbt models or BI dashboards silently break.
When to use it
You own downstream models that read from tables a different team (or an ingestion tool) controls. You want a heads-up the day a column moves, not a 2am pager when a dashboard returns nulls.
How it works
- 1A scheduled trigger fires every morning.
- 2Query `INFORMATION_SCHEMA.COLUMNS` in Snowflake for each watched table, collecting name, type, and nullability.
- 3Load the previous snapshot from Postgres and diff it against the fresh one.
- 4A logic step checks whether any column was added, removed, or retyped.
- 5If drift is found, post a Slack message listing each change with the table and the before/after.
- 6Write the new snapshot back to Postgres so the next run compares against today.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Data Ops workflows
BigQuery Per-Team Budget Breach Alert to PagerDuty
Tracks month-to-date BigQuery scheduled-query spend per team and, when a team crosses its monthly budget, pages the team's on-call in PagerDuty and snapshots the spend breakdown…
dbt orphan model detector with Linear cleanup tickets
Scans your dbt manifest for models that no other model, exposure, or BI tool consumes.
Weekly BigQuery Cost Trend Sheet and Exec Digest
Compiles week-over-week BigQuery scheduled-query cost by owner and dataset into a Google Sheet with trend columns.
Backfill Missing Owner Labels on BigQuery Scheduled Queries
Finds scheduled queries with no owner label, infers the likely owner from creator metadata and target-table lineage, proposes a label.
Daily BigQuery Scheduled-Query Cost Attribution to Owners
Each morning, totals the prior day's on-demand bytes-billed per scheduled query, maps each query to its owner from a label, and posts a per-owner cost leaderboard to Slack.
dbt source freshness watcher with severity-routed alerts
Checks Snowflake loaded-at timestamps against each dbt source's freshness SLA, then routes warnings to Slack and hard breaches to a PagerDuty incident so stale data never…
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.